S1 Data -

This study constructed a multidimensional indicator system to evaluate spatio-temporal heterogeneity of China’s import and export trade of 31 provinces from 2000 to 2022. This study describes the distribution of China’s import and export trade by using location Gini coefficient and exploratory spatial analysis. Additionally, Multiple linear regression was used to ascertain the extent of contribution by various factors on the spatio-temporal heterogeneity of import and export trade. The simulation results show that inter-provincial import and export trade displayed distinct spatio-temporal differentiation characteristics with a prominent east-to-west disparity from 2000 to 2022. The trade links between various regions of the country have gradually strengthened, with a corresponding high correlation to the level of economic development. GDP, financial expenditure, freight transportation volume, technology market turnover, foreign investment, and disposable income of all residents, significantly influence the per capita export and import volume. In general, it is suggested that China and developing countries should take effective measures to promote balanced trade development, strengthen regional cooperation and coordination, and promote green trade and sustainable development.

本研究构建了多维指标体系，用以评估2000年至2022年中国31个省份进出口贸易的时空异质性。本研究采用区位基尼系数（location Gini coefficient）与探索性空间分析（exploratory spatial analysis）方法，刻画中国进出口贸易的空间分布格局。此外，本研究借助多元线性回归（multiple linear regression）模型，厘清各类因素对进出口贸易时空异质性的贡献程度。模拟结果显示，2000年至2022年，中国省际进出口贸易呈现显著的时空分异特征，东西部差距尤为突出。全国各区域间的贸易联系逐步强化，且与区域经济发展水平呈现较强的正相关性。GDP、财政支出、货运量、技术市场成交额、外商直接投资额以及全体居民可支配收入，均对人均进出口额产生显著影响。总体而言，建议中国及广大发展中国家采取有效举措，推动贸易均衡发展，强化区域合作与协同联动，促进绿色贸易与可持续发展。